10th International Congress on Information and Communication Technology in concurrent with ICT Excellence Awards (ICICT 2025) will be held at London, United Kingdom | February 18 - 21 2025.
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Authors - Reena (Mahapatra) Lenka, Smita Mehendale Abstract - This research paper examines this combination to understand better how Artificial Intelligence (AI) and Extended Reality (XR) might work together to change human experiences and capacities. Enhancing immersive environments primarily depends on artificial intelligence (AI), miming human cognitive capabilities. The study conducts a thorough literature review to comprehend the AI-XR synergy's goals, uses, constraints, and viewpoints. It emphasises how AI may complement human labour and how XR can produce multi-dimensional experiences, using examples from the aerospace, construction, and healthcare sectors. The paper describes the influence of these technologies on the nature of work in the future. Also, it focuses on the necessity for companies to create strategies that take advantage of both possibilities and problems. To effectively recruit and develop the talents necessary to merge human and machine efforts in modern workplaces, the H.R. role is growing.
Authors - Byron Albuja-Sanchez, Jeniffer Flores-Toala, Arcesio Bustos-Gaibor, Sandra Arias-Villon Abstract - The problem with predicting a possible risk of fetal death is that it depends on several aspects, not only medical but also economic and social aspects of the pregnant mothers, which makes an early response to this problem very difficult. This work seeks to apply classification algorithms to detect the risk of fetal death based on socioeconomic and demographic data of pregnant mothers in Ecuador, using datasets from 2000 to 2021. Trained algorithms include decision trees, random forests, neural networks, bagging classifiers, k nearest neighbors, and naive bayes bernoulli. As cases of fetal death are very rare, over-sampling and undersampling techniques were applied to train the algorithms. The performance comparison of the trained algorithms was carried out with their respective confusion matrices. The best performance was obtained by the algorithms trained with undersampling and of all of them the performance of the neural network stood out. The best performance of the neural network was associated with its nature of classifying by assigning weights to each input parameter.
Authors - Christos Chronis, Iraklis Varlamis, Konstantinos Tserpes, George Dimitrakopoulos, Faycal Bensaali Abstract - This paper introduces an innovative architecture for deploying AI models in edge and cloud environments, leveraging Federated Learning and RISC-V processors for privacy and real-time inference. It addresses the constraints of edge devices like Raspberry Pi and Jetson Nano by training models locally and aggregating results in the cloud to mitigate overfitting and catastrophic forgetting. RISC-V processors enable high-speed inference at the edge. Applications include energy consumption monitoring with LSTM models and recommendations via collaborative filtering, and multi-robot human collaboration using CNN and YOLO models. Model compression and partitioning optimize performance on RISC-V, with experiments demonstrating scalability and responsiveness under varying computational demands.
Authors - Joyce Wong Ching Yan, Davy Tsz Kit Ng Abstract - This chapter investigates the effects of generative artificial intelligence and digital transformation on K-16 school leaders in the post-pandemic period. It describes the challenges those leaders face in the technology integration processes and recommends developing AI competencies, interdisciplinary curricula and relevant leadership skills. The shift to learning over the Internet as a consequence of the actions that were taken towards the prevention of the spread of covid 19 brought many positives but many education managers continue to face the challenges of educational technology integration. Such factors include the influence of wonderful ideas and the provision of working rooms that encourage teacher collaboration. The chapter proposes plans for creating professional development furthering teachers’ modernization of their digital knowledge. It also addresses the aspect of the efficient digital design that helps implement contemporary curricular programs. As soon as they pay attention to these most important items, their schools will be more able to meet the needs of the digital world market, and consequently enhance the students’ performance. This chapter adds further discussion of initiatives and projects on school leadership and technology communication integration. It describes specific techniques relevant to today's education and the issues that they face as the environment changes rapidly.
Authors - Mohammad Hamzehloui, Ardavan Ashabi Abstract - Microservices have emerged as a preferred architectural style for developing scalable and resilient applications, especially within cloud environments. This approach offers significant advantages over traditional monolithic architectures, such as enhanced scalability, flexibility, and fault isolation. However, these benefits come with substantial operational costs. Running microservices on cloud platforms incurs high expenses due to the need for extensive monitoring, complex service management, and dynamic resource allocation. Industry solutions have primarily focused on monitoring and management, leaving a gap in comprehensive strategies for cost reduction through optimization and resource management. This study aims to identify and analyze the primary cost drivers of running microservices and assess their individual impacts. By providing a detailed analysis, this research enhances the understanding of cost factors, aiding in the cost management and optimization of cloud-based microservices. This knowledge helps businesses make informed decisions to minimize expenses while maximizing the benefits of cloud adoption. Key cost drivers identified include virtualization mechanisms, scaling solutions, microservice architectures, API designs. Microservices vary significantly in terms of performance and resource consumption depending on their design and architecture. However, by following certain best practices, it is possible to reduce the overall running costs of microservices by minimizing resource consumption.
Authors - Rachel Roux, Sonia Yassa, Olivier Romain Abstract - Cloud computing is widely used to collect data from various devices, which must be processed quickly. To manage this growing data, fog computing helps reduce delay and processing costs by assigning tasks to suitable devices. This article presents an adapted binary monarch butterfly algorithm for task offloading in a fog-cloud environment. This metaheuristic directly constructs a Pareto front, offering a solution space representation. Two versions are examined: one using random search and the other a deterministic search with crowding distance. Simulations on tasks from 40 to 500 show that the binary Monarch Butterfly algorithm can outperform state-of-the-art algorithms for cost optimization while balancing delay.
